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Exploring the Capabilities of ChatGPT

Throughout the video, I navigate through a spreadsheet, extract data, and generate reports using ChatGPT.

Updated over a year ago


In this video, we provide a demonstration of ChatGPT-4, highlighting its advanced features and practical applications. We explain that ChatGPT-4 is a paid version, costing $20 US, and it allows for file uploads, focusing on CSV files. We demonstrate how ChatGPT-4 can analyze sales data from CSV exports, identifying top-selling products and performing calculations like summing up columns for total sales.

We show ChatGPT-4's ability to generate insights from data, such as comparing orders placed by club members and non-members, and identifying top-spending clubs. We upload different CSV files and guide ChatGPT-4 to use specific columns for accurate results.

Additionally, we check ChatGPT-4's outputs against traditional methods like pivot tables and VLOOKUP in Excel, confirming its accuracy. We also illustrate ChatGPT-4's capability in generating content, such as writing tasting notes for a wine and adapting the language for different audiences.

Video Transcript

00:00 Hey guys, today we're going to go through ChatGPT, wanted to give you a bit of a show-and-tell. So ChatGPT, a lot of you would have heard about it obviously, but maybe some of you hadn't seen it. 00:12 So I thought I'd show some of its capabilities to you and how it might work. May help you just get through some of the day-to-day things that you want to do. 00:21 Now I will highlight that we're using ChatGPT 4 here instead of ChatGPT 3.5. So 4 is a paid version of ChatGPT. 00:31 It's $20 US. It does more. That's why you're paying for it. So you can upload files and whatnot. But the free version, you can still talk to it. 00:41 But ChatGPT 4 lets you upload files. And when I'm talking about uploading files in particular I'm talking about CSV exports. 00:51 So what we can do is go into with wine and say, right, I want to see all orders for this year and I want to get my order items. 01:05 CSV, right? So we'll download that. So that's giving us the total export of things sold during the year. Now what I'm going to do is I'm going to get that export and I'm going to say what is the, ah, actually let's just go see what are my top selling products. 01:36 And so what it's doing is going into the spreadsheet and it's saying right it's what it's doing now it's going through the columns and saying I think I'm going to use these columns to get the answer that you need. 01:56 And sometimes you've got to give it a helping hand right so sometimes it doesn't know which column in particular you might want to use but there you go, dollar wine, Riesling, boom boom boom. 02:12 And then we can say for the dollar values can you, so we can just do a check because what we want to do is we want to make sure in this CSV. 02:25 We want to make sure it's using not the gross, we want to see item total pricing there. So we want to make sure it's adding up that column. 02:39 Can you use that column? For the totals. And so we can just check that it is actually using the correct column. 02:51 It probably did, but we just want to check. And instead of going into this blind and saying hey do this you can actually say give me this total using these columns for the dollar value. 03:08 There you go. So that's cleaned it up, see? So 10,146 got that right the first time. But that's using the total value of the order. 03:19 And this CSV has multiple rows per order. So there you go, there's your total dollar sales per, ah, per product. 03:30 Now, let's do something else. So we'll go back into With Wine. And what we're gonna do is just do a orders CSV, a basic one which doesn't go into the row by row detail. 03:43 Ah, so we're gonna upload that. And we're also, so we're gonna say using Thanks for watching. Let's go again, get the right column. 04:12 So we want, we don't want the gross, we want the net. So using d-d-d-d, what, ah, what are my total orders, now that's just going to obviously add up that column which should be 292,976. 04:45 There you go. Now we can say, now let's do this. I'm going to upload a CSV of my club members. 05:08 Using the email address. Tell me Tell me how, Actually, no, we'll do this. Show me a pie chart of the break down. 05:41 Actually here. Show me a pie chart of orders placed by club members versus orders placed by club members. So now it's getting the second CSV. 06:07 I've told it to use the email address as the customer identifier and so now it's going to go into the orders CSV, use that identifier and start giving me some totals. 06:22 I'll give it a couple more seconds. There you go. Pretty cool. Now what you can probably also do is say which clubs are they members of actually for those placing, ah, for those members placing orders, ah, show me See you next time. 06:57 Bye. Clubs, that's off. Now I haven't told it which column in the, I haven't told them which column in the, in the club CSV there, is the column saying what the name of the club is, ah, so let's see if it works that out, bye. 07:16 There you go, so, but here it's trying again. So let's go in, fair enough. Ah yeah, because I've got a lot of clubs only show. 08:20 The top five clubs. This is just from our, from our dummy testing environment. So we've got lots of clubs. And there you go. 08:34 So, yeah, as I said, I just wanted to give you a bit of a demonstration of what you can do from a reporting perspective. 08:45 Let's just try one more thing. Let's say who are my top spending clubs. Because obviously it's got the two, it's got the two CSVs. 08:59 Now the order CSV doesn't say whether it's a club member or not, but the club member CSV does, so it's comparing the data between the two. 09:11 There you go. And there's your totals. Now let's actually, why don't we do a check of that just to make sure it's not making things up. 09:22 So, what we're gonna do, See? We'll close that one because we don't need that anymore. So, we're gonna get the email address. 09:33 So we'll do this the old way, is member. Cool. And we'll go into the club members, extract. Where was that? 09:49 Where did I put that? This one. Copy all of that. No. Paste that. Oops. No, I didn't copy it. That, that. 10:09 Copy. Paste. I don't need that column, so I'll just delete that. So I'm going to say this is a, so do a V look up, looking up this value in, Oh, actually, sorry. 10:30 Just what I'll do is I'll just go here, call this, call this members and we won't call them three. So we'll go equals V look up. 10:45 So we're looking up this value in members. We want to retrieve column three and we want it to be exact match. 10:59 Boom. So now we'll get this and we'll do a pivot table. Okay. So now we'll say. So we use the email address is members of filter and we'll use the. 11:34 Order total sales net. Okay. So we're going to filter out the club members. I'm sorry. Filter out the non club members. 11:44 There we go. And we'll get this and just so that we. We can sort it. We'll chuck it in a new spreadsheet and we'll go data. 11:56 Whoops. Not filter. Whoops. Cancel, cancel, cancel. Get out of that. Okay. Data filter sort. I mean data sort by column B largest to smallest. 12:06 Hit OK. Okay. There we go. Here are our totals. So let's see how we compare with chat GPT. So Adrian 11, 126. 12:19 Okay. It's probably, there you go. So it's using that's the same. That's the same. That's the same. Yeah. So there you go. 12:28 Now I'm not sure where it's getting the extra hundred dollars. It's getting another hundred dollars from somewhere. So I'm not sure where, but for a quick, example of how you can get some information out if you see it. 12:45 So I think it's pretty cool. Now just while I'm here, cause I've got to finish up, but one thing extra I'll show you with chatgbt is let's say I've got a I've got to do some content from my website. 12:59 So let's say we're visiting a winery in the Hunter Valley. So we say I own a winery in the Hunter Valley. 13:12 Called, I don't know, let's pick a winery. Peterson's. I sell a back-lock Shiraz. I've just released, the 2023 vintage, and I'd like you to write the tasting notes. 13:40 Please also include, some vintage notes. Let's see what it says. Now the thing is, is one thing you've got to be careful with chatgbt especially at the moment is that sometimes it does make this up. 14:10 Right? So some of this may or may not be off. Remembering that it's data only goes back to the end. A certain date as well. 14:18 But in general, you can, I just wanted to show an example of how you can use it to get through things quicker. 14:27 Now actually let's just look at this tasting note, right? So. Purple hues. Now what we can do is say that's a little bit too wine nerd. 14:44 Can you rewrite? For a layman. Here you go. So, pretty cool. So, now the thing is, is that chatgbt Take care. 15:20 It has APIs. Yes, we're mucking around with them, seeing what we can do, but as I said, wanted to give you a bit of a flavor of what it can do, remembering that I did have a specific question of, you know, how can I extract this information? 15:33 And my answer was, well, you can do pivot tables and vlookups using the CSVs, but I wanted to make this video to show that you can actually use chatgbt, which does the work for you quicker and easier. 15:46 So that's what I wanted to share and I hope you found it useful. Thanks, bye.

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